#!/usr/bin/env python
if __name__ != '__main__': raise Exception("Do not import me!")
import sys
sys.path.insert(0, "..")

try:
	from yaml import CLoader as Loader, CDumper as Dumper
except ImportError:
	from yaml import Loader, Dumper

import yaml
import logging
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle

from argparse import ArgumentParser

from nabirds import CUB_Annotations

def init_logger(args):
	fmt = "%(levelname)s - [%(asctime)s] %(filename)s:%(lineno)d [%(funcName)s]: %(message)s"
	logging.basicConfig(
		format=fmt,
		level=getattr(logging, args.loglevel.upper(), logging.DEBUG),
		filename=args.logfile or None,
		filemode="w")


def plot_crops(crops, title, scatter_mid=False, names=None):

	n_crops = crops.shape[0]
	rows = int(np.ceil(np.sqrt(n_crops)))
	cols = int(np.ceil(n_crops / rows))

	fig, axs = plt.subplots(rows, cols, figsize=(16,9))
	fig.suptitle(title, fontsize=16)
	for i, crop in enumerate(crops):
		ax = axs[np.unravel_index(i, axs.shape)]
		if names is not None:
			ax.set_title(names[i])
		ax.imshow(crop)
		ax.axis("off")
		if scatter_mid:
			middle_h, middle_w = crop.shape[0] / 2, crop.shape[1] / 2
			ax.scatter(middle_w, middle_h, marker="x")


def main(args):
	init_logger(args)

	annot = CUB_Annotations(
		args.info, args.parts, args.feature_model)

	logging.info("Loaded data from \"{}\"".format(annot.root))

	uuids = getattr(annot, "{}_uuids".format(args.subset))

	data = annot.new_dataset(
		args.subset,

		crop_to_bb=args.crop_to_bb,
		crop_uniform=args.crop_uniform,

		parts_in_bb=args.parts_in_bb,

		rnd_select=args.rnd,
		seed=args.seed
	)

	logging.info("Loaded {} {} images".format(len(data), args.subset))

	start = max(args.start, 0)
	n_images = min(args.n_images, len(data) - start)

	for i in range(start, max(start, start + n_images)):
		im, parts, label = data[i]

		fig1, axs = plt.subplots(2, 1, figsize=(16,9))
		axs[0].axis("off")
		axs[0].set_title("Visible Parts")
		axs[0].imshow(im)
		if not args.crop_to_bb:
			data.plot_bounding_box(i, axs[0])
		parts.plot(im=im, ax=axs[0], ratio=data.ratio)

		axs[1].axis("off")
		axs[1].set_title("{}selected parts".format("randomly " if args.rnd else ""))
		axs[1].imshow(parts.reveal(im, ratio=data.ratio))

		if data.uniform_parts:
			crop_names = None
		else:
			crop_names = list(data._annot.part_names.values())

		part_crops = parts.visible_crops(im, ratio=data.ratio)
		if args.rnd:
			parts.invert_selection()
			action_crops = parts.visible_crops(im, ratio=data.ratio)

		plot_crops(part_crops, "Selected parts", names=crop_names)

		if args.rnd:
			plot_crops(action_crops, "Actions", names=crop_names)

		plt.show()
		plt.close()


parser = ArgumentParser()

parser.add_argument("info")

parser.add_argument("--parts", "-p",
	choices=["GT", "GT2", "NAC", "UNI", "L1_pred", "L1_full"]
)

parser.add_argument("--feature_model", "-fm",
	choices=["inception", "inception_tf", "resnet"]
)

parser.add_argument("--subset", "-sub",
	help="Possible subsets: train, test",
	choices=["train", "test"],
	default="train", type=str)


parser.add_argument("--start", "-s",
	help="Image id to start with",
	type=int, default=0)

parser.add_argument("--n_images", "-n",
	help="Number of images to display",
	type=int, default=10)



parser.add_argument("--rnd",
	help="select random subset of present parts",
	action="store_true")

parser.add_argument("--crop_to_bb",
	help="Crop image to the bounding box",
	action="store_true")

parser.add_argument("--crop_uniform",
	help="Try to extend the bounding box to same height and width",
	action="store_true")

parser.add_argument("--parts_in_bb",
	help="Only display parts, that are inside the bounding box",
	action="store_true")


parser.add_argument(
	'--logfile', type=str, default='',
	help='File for logging output')

parser.add_argument(
	'--loglevel', type=str, default='INFO',
	help='logging level. see logging module for more information')

parser.add_argument(
	'--seed', type=int, default=12311123,
	help='random seed')

main(parser.parse_args())